An Intelligent Educational System for Breast Cancer Management | ||
| International Journal of Intelligent Computing and Information Sciences | ||
| Article 16, Volume 22, Issue 3, August 2022, Pages 39-53 PDF (1.13 M) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/ijicis.2022.136628.1179 | ||
| Author | ||
| نجوي Ù…Øمد عبدالعال* | ||
| قسم Øاسب الي کلية تربية نوعية جامعة المنصورة | ||
| Abstract | ||
| Abstract This paper introduces an intelligent system for breast cancer management for helping new and young healthcare graduates. The proposed system simulates the real medical diagnosis processes by using artificial intelligence (AI) techniques. It is based on four parts for breast cancer management. The first part is based on diagnosing by symptoms of breast cancer. The second part is based on x-ray images in the diagnosis process. The third part is based on the results of breast biopsy in the diagnosis process. The fourth part introduces the suitable treatment based on the stages of breast cancer. The experimental results show high efficiency of the proposed system for helping in diagnosis and treatment. As computer technology has advanced, more sophisticated technologies to aid medical practitioners in making decisions have been developed by software engineers and subject knowledge specialists . Because the relationship between disease and symptoms is rarely one-to-one in medicine, the range of symptoms is inherently challenging for new doctors. Human knowledge and reasoning skills would be used by an intelligent system to solve real-world problems . Expert systems, referred to as knowledge-based systems, are the most common artificial intelligence systems used in the therapeutic setting. They are medically trained, generally for a specific role, and therefore can provide possible explanations with data to arrive at rational conclusions. Although there are numerous variations, the knowledge of an expert system is described as a collection of rules. | ||
| Keywords | ||
| knowledge base; image processing; intelligent systems; breast cancer; expert systems | ||
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